Costable — Parametric Should-Cost Analysis MCP Server

by 1337mofo Your server? Claim it

answering

Costable — Parametric Should-Cost Analysis is answering right now. Last checked 5 min ago. It exposes 10 tools.

Parametric should-cost: P50/P80/P90 estimates, 801 materials, 25 countries, quote review.

Uptime history 19 days of history

19 days agonow

100.0%

Uptime 24h

93 of 93 checks

Tools

read from the server

1076 ms

Response time

average over 24h

open, no key

Access

streamable-http

Nothing serious here today

Today is the operative word: we check Costable — Parametric Should-Cost Analysis every 15 minutes and re-read its code on every release. Watch it and you find out the day that stops being true.

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 5 min ago.

Claude Code Claude Desktop Codex Cursor VS Code

run in your terminal

claude mcp add costable --transport http https://costable.ai/api/mcp

~/Library/Application Support/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "costable": {
      "url": "https://costable.ai/api/mcp"
    }
  }
}

~/.codex/config.toml

[mcp_servers.costable]
url = "https://costable.ai/api/mcp"

.cursor/mcp.json

{
  "mcpServers": {
    "costable": {
      "url": "https://costable.ai/api/mcp"
    }
  }
}

.vscode/mcp.json

{
  "mcpServers": {
    "costable": {
      "url": "https://costable.ai/api/mcp"
    }
  }
}

Available tools 10

Read directly from the server with tools/list, grouped by what they act on. If a tool disappears, we record the date.

calculate

calculate_cost_model

Run the Monte Carlo should-cost calculation on a cost model. Returns P50 (median), P80 and P90 cost-at-risk per unit, plus a full cost breakdown (material, labour, machine, overhead, margin).

compare

compare_manufacturing_countries

Run the cost model across multiple manufacturing countries simultaneously to identify the optimal sourcing location. Returns P50/P80/P90 per country and % delta vs baseline.

cost

create_cost_model

Create a new parametric cost model in Costable. Returns the model ID which is used by add_material_to_model, add_process_to_model, calculate_cost_model, and compare_manufacturing_countries.

estimate

estimate_part

Instantly estimate the should-cost of a manufactured part using natural language. Returns P50 (median), P80 and P90 cost-at-risk per unit based on Monte Carlo simulation of material price variance, labour rate variance and cycle time uncertainty. Use this for quick feasibility checks before building a full cost model.

labour

get_labour_rates

Get manufacturing labour rates ($/hr) for all skill levels in a given country. Data covers 16 skill levels across 25 countries (ILO/BLS/ABS sourced).

material

add_material_to_model

Add a material (BOM line) to an existing cost model. Searches the materials database by name query — no need for exact IDs.

materials

search_materials

Search the Costable materials database (37 materials with LME-sourced pricing). Returns material name, category, price per kg, density, and strength properties.

process

add_process_to_model

Add a manufacturing process step to an existing cost model. Searches the process database by name query — no need for exact IDs.

processes

search_processes

Search the Costable manufacturing process database (41 processes). Returns process name, category, machine rate ($/hr), and cycle time model.

review

review_supplier_quote

Analyse a supplier quote against Costable's should-cost benchmarks. Returns a line-by-line delta (% over/under should-cost), verdict (LOW / COMPETITIVE / HIGH / VERY HIGH), and a list of the top items to challenge in negotiation.

Endpoints

URL	Transport	State	Latency	Checked
https://costable.ai/api/mcp	streamable-http	answering	866 ms	5 min ago

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Costable — Parametric Should-Cost Analysis — questions

Answers built from our own checks of this server.

What can Costable — Parametric Should-Cost Analysis do?

It exposes 10 tools, read directly from the server on our last check. Among them: add_material_to_model, add_process_to_model, calculate_cost_model, compare_manufacturing_countries, create_cost_model, estimate_part and 4 more. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README. How MCP servers expose tools in the first place →

Is Costable — Parametric Should-Cost Analysis working right now?

We send a real MCP handshake every 15 minutes. Over the last 24 hours 93 of 93 checks got a reply (100.0%), average response time 1076 ms. The bar chart above shows every period we have measured.

How do I connect Costable — Parametric Should-Cost Analysis?

Copy the ready config from this page — we generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each with the file path that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.

Does Costable — Parametric Should-Cost Analysis need an API key?

No. Costable — Parametric Should-Cost Analysis completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 10 of them are readable on this page. This is what we observed, not what the docs claim.

How fast is Costable — Parametric Should-Cost Analysis?

It answers our handshake in 1076 ms on average, which is faster than 7% of all working MCP servers we measure. That is on the slow side — worth knowing if the tool sits inside an interactive loop. The comparison comes from our own checks across the whole registry, every 15 minutes.